RunFuseNet: Run Data Fusion

In stevexniu/FuseNet: Non-Parametric Network Fusion

Run Data Fusion

Description

Run Data Fusion.

Usage

RunFuseNet(
  object,
  n_iters = 100,
  ratio = 0.05,
  pca_dims = 0,
  k = 100,
  t = 0,
  norm_type = c("l1", "l2"),
  return_perturb_mat = FALSE,
  n_cores = NULL,
  ...
)

Arguments

object	A FuseNet object.
n_iters	Number of bootstrapping iterations. Default is 100.
ratio	Fraction of features to be downsampled in the original data matrix. Default is 0.05 aka 5%.
pca_dims	Number of principle components. Default is 0 and PCA is not run.
k	Number of nearest neighbors used. Default is 100.
t	Matrix power used for the distance matrix. Default is 0 and powering is not performed.
norm_type	Type of norm used: l1, L1-like norm. See details L1Norm. l2, L1-like norm. See details L2Norm.
return_perturb_mat	Whether to return the perturb matrix. Default is FALSE.
n_cores	Number of cores used. Default is to use all existing cores. See details makeCluster.
...	Additional parameters pass to makeCluster.

Value

Returns a FuseNet object.

Examples

{
object <- InitiateFuseNet(t(iris[,1:4]), project_name = "FuseNet", k = 3)
object <- RunFuseNet(object, n_iters = 1, k = 10, ratio = 0.5, n_cores = 1)
}

stevexniu/FuseNet documentation built on May 16, 2022, 12:23 p.m.